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arxiv: 2504.19790 · v1 · submitted 2025-04-28 · ❄️ cond-mat.soft · physics.comp-ph· q-bio.BM

TDP-43 multidomains and RNA modulate interactions and viscoelasticity in biomolecular condensates

Yui Matsushita , Ikki Yasuda , Fuga Watanabe , Eiji Yamamoto This is my paper

Pith reviewed 2026-05-22 18:33 UTC · model grok-4.3

classification ❄️ cond-mat.soft physics.comp-phq-bio.BM
keywords TDP-43biomolecular condensatesphase separationviscoelasticityRNA bindingmolecular dynamicsmultidomain proteinsintrinsically disordered regions
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The pith

RNA binding to TDP-43 replaces some protein-protein contacts with protein-RNA contacts and shifts condensate viscosity and elasticity.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper uses molecular dynamics simulations to examine how the multidomain architecture of TDP-43, consisting of an IDR plus folded RRMs and NTD, interacts with polyA RNA during phase separation. It shows that RNA binding drives a rearrangement of interaction sites in the IDR, replacing several TDP-43 intermolecular contacts with TDP-43-RNA contacts. This rearrangement produces measurable changes in condensate mechanics: RRMs raise viscosity while the NTD lowers it, and polyA raises elasticity until the two properties reach comparable magnitudes. These results matter to a sympathetic reader because they link specific molecular features to the physical behavior that governs condensate function in cells.

Core claim

Our analysis reveals that interaction sites within the IDR undergo dynamic rearrangement, driven by key residues that depend on the specific combination of folded domains. Upon RNA binding, several intermolecular interactions of TDP-43 are replaced by TDP-43-polyA interactions, altering viscoelastic properties of the condensate. Specifically, RRMs enhance viscosity, whereas the NTD reduces it. The presence of polyA increases elasticity, making viscosity and elasticity comparable in magnitude. These findings suggest that the multidomain structure of TDP-43 and its RNA interactions orchestrate condensate organization, modulating their viscoelastic properties.

What carries the argument

Dynamic rearrangement of interaction sites inside the IDR, controlled by the combination of RRMs, NTD, and polyA RNA.

If this is right

  • RRMs raise the viscous response of the condensate.
  • The NTD lowers the viscous response of the condensate.
  • PolyA RNA raises elasticity until it becomes comparable to viscosity.
  • The specific mix of domains and RNA determines which residues dominate the rearranged interaction network.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Cells could adjust condensate mechanics by altering the relative expression of TDP-43 domains or the local RNA concentration.
  • Analogous domain-RNA competition may set material properties in condensates formed by other multidomain RNA-binding proteins.
  • Domain-specific mutations could be introduced in vitro to test whether targeted changes in viscosity or elasticity alter condensate fusion or cargo retention.

Load-bearing premise

The molecular-dynamics force fields and simulation lengths used here correctly reproduce the real dynamic rearrangement of interaction sites and the resulting macroscopic viscoelastic response.

What would settle it

A microrheology or oscillatory measurement on TDP-43 condensates that finds no increase in the ratio of elastic to viscous moduli when polyA is added, or no opposite viscosity shifts when RRMs or NTD are removed.

Figures

Figures reproduced from arXiv: 2504.19790 by Eiji Yamamoto, Fuga Watanabe, Ikki Yasuda, Yui Matsushita.

Figure 1
Figure 1. Figure 1: FIG. 1. Phase separation of TDP-43 with different domain constructs. (A) Representative structure of full-length TDP-43 [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Molecular interactions within TDP-43 and between TDP-43 and polyA. (A) Probability density functions of the radius [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Viscoelasticity of condensates. (A) Shear modulus of TDP-43 condensates without polyA and (B) with polyA. The [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Schematic of molecular interaction rearrangements depending on the domain construct and the presence of RNA in [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
read the original abstract

RNA-binding proteins form biomolecular condensates with RNA through phase separation, playing crucial roles in various cellular processes. While intrinsically disordered regions (IDRs) are key drivers of phase separation, additional factors such as folded domains and RNA also influence condensate formation and physical properties. However, the molecular mechanisms underlying this regulation remain elusive. Here, using molecular dynamics simulations, we investigate how the multidomain structure of TDP-43, which consists of its IDR, RNA recognition motifs (RRMs), and N-terminal domain (NTD), interacts with RNA and affects the characteristics of phase separation. Our analysis reveals that interaction sites within the IDR undergo dynamic rearrangement, driven by key residues that depend on the specific combination of folded domains. Upon RNA binding, several intermolecular interactions of TDP-43 are replaced by TDP-43-polyA interactions, altering viscoelastic properties of the condensate. Specifically, RRMs enhance viscosity, whereas the NTD reduces it. The presence of polyA increases elasticity, making viscosity and elasticity comparable in magnitude. These findings suggest that the multidomain structure of TDP-43 and its RNA interactions orchestrate condensate organization, modulating their viscoelastic properties.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript uses molecular dynamics simulations to examine how the multidomain architecture of TDP-43 (IDR, RRMs, and NTD) interacts with polyA RNA and modulates intermolecular contacts and the viscoelastic properties of biomolecular condensates. It reports dynamic rearrangement of IDR interaction sites depending on the presence of folded domains, replacement of TDP-43 intermolecular interactions by TDP-43-polyA contacts upon RNA binding, RRMs increasing viscosity, the NTD decreasing viscosity, and polyA increasing elasticity until the two moduli become comparable in magnitude.

Significance. If the reported domain-specific effects on viscosity and elasticity are robust, the work would provide useful molecular insight into how folded domains and RNA tune condensate mechanics in TDP-43 systems, with potential relevance to ALS/FTD pathology. The direct linkage of specific domains to changes in interaction networks and macroscopic moduli is a positive feature, though the absence of methodological validation for the viscoelastic calculations limits current impact.

major comments (2)
  1. [Methods] Methods section: No force field, system size, equilibration protocol, or error estimation procedure is described for the MD trajectories used to compute viscosity and elasticity. This is load-bearing because force-field inaccuracies in π–π or cation–π contacts are known to invert relative interaction strengths in IDR condensates, directly affecting the claimed replacement of TDP-43 contacts by TDP-43-polyA interactions and the domain-specific viscosity trends.
  2. [Results] Results (viscoelastic properties subsection): The manuscript provides no data on the length of the production trajectories or on whether the stress autocorrelation functions have decayed to yield converged zero-shear viscosity and storage modulus. Given that relaxation times in disordered-protein condensates frequently exceed 1 µs, this omission prevents assessment of whether the reported comparability of viscosity and elasticity upon polyA addition is reliable or an artifact of insufficient sampling.
minor comments (2)
  1. [Abstract] Abstract: The abbreviation 'polyA' should be expanded on first use for clarity.
  2. [Figures] Figure captions: Several panels lack error bars or indication of the number of independent runs used to generate the reported interaction counts and modulus values.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us identify areas where the manuscript can be improved for greater clarity and rigor. We have revised the manuscript to address the concerns about methodological details and the validation of viscoelastic calculations.

read point-by-point responses

  1. Referee: [Methods] Methods section: No force field, system size, equilibration protocol, or error estimation procedure is described for the MD trajectories used to compute viscosity and elasticity. This is load-bearing because force-field inaccuracies in π–π or cation–π contacts are known to invert relative interaction strengths in IDR condensates, directly affecting the claimed replacement of TDP-43 contacts by TDP-43-polyA interactions and the domain-specific viscosity trends.

    Authors: We agree that these methodological details were insufficiently described in the original submission. In the revised manuscript, we have substantially expanded the Methods section to specify the force field, system sizes and compositions for each construct, the full equilibration and production protocols, and the error estimation procedures (including block averaging across independent replicas). We have also added a brief discussion acknowledging known limitations of current force fields for π–π and cation–π interactions while emphasizing that our primary conclusions rely on relative changes across domain combinations and RNA conditions rather than absolute interaction energies. revision: yes

  2. Referee: [Results] Results (viscoelastic properties subsection): The manuscript provides no data on the length of the production trajectories or on whether the stress autocorrelation functions have decayed to yield converged zero-shear viscosity and storage modulus. Given that relaxation times in disordered-protein condensates frequently exceed 1 µs, this omission prevents assessment of whether the reported comparability of viscosity and elasticity upon polyA addition is reliable or an artifact of insufficient sampling.

    Authors: We thank the referee for this important observation. In the revised manuscript, we now report the lengths of the production trajectories and include supplementary figures of the stress autocorrelation functions demonstrating their decay. We have added text confirming that the functions reach near-zero values within the sampled time and that the resulting zero-shear viscosity and storage modulus values are stable when computed over different trajectory segments, supporting the reliability of the observed shift toward comparable viscosity and elasticity upon polyA addition. revision: yes

Circularity Check

0 steps flagged

No circularity: claims rest on direct MD simulation outputs

full rationale

The paper reports molecular dynamics simulations of TDP-43 multidomain constructs with and without polyA RNA. Interaction rearrangements and viscoelastic changes (RRMs increasing viscosity, NTD decreasing it, polyA increasing elasticity) are extracted as direct observables from the trajectories. No equations, fitted parameters, or self-citations are presented that redefine inputs as outputs or force predictions by construction. The derivation chain is computational and self-contained against external benchmarks such as force-field validation and experimental condensate rheology; it does not reduce to tautological renaming or self-referential fitting.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Central claims rest on the validity of classical MD for capturing condensate rheology and on the assumption that observed contact rearrangements directly determine macroscopic viscosity and elasticity; no free parameters or new entities are named in the abstract.

axioms (1)
  • domain assumption Standard biomolecular force fields and simulation protocols sufficiently reproduce the equilibrium structure and dynamics of TDP-43-RNA condensates on accessible timescales.
    The entire analysis is performed via MD; any mismatch between model and reality would invalidate the reported domain-specific effects on viscoelasticity.

pith-pipeline@v0.9.0 · 5751 in / 1376 out tokens · 50446 ms · 2026-05-22T18:33:21.379248+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

66 extracted references · 66 canonical work pages

  1. [1]

    Shin and C

    Y. Shin and C. P. Brangwynne, Science 357, eaaf4382 (2017)

    work page 2017

  2. [2]

    M. M. Fay and P. J. Anderson, J. Mol. Biol. 430, 4685 (2018)

    work page 2018

  3. [3]

    J.-Y. Youn, B. J. Dyakov, J. Zhang, J. D. Knight, R. M. Vernon, J. D. Forman-Kay, and A.-C. Gingras, Mol. Cell 76, 286 (2019)

    work page 2019

  4. [4]

    H. J. Wiedner and J. Giudice, Nat. Struct. Mol. Biol. 28, 465 (2021)

    work page 2021

  5. [5]

    G. M. Wadsworth, S. Srinivasan, L. B. Lai, M. Datta, V. Gopalan, and P. R. Banerjee, Mol. Cell 84, 3692 (2024)

    work page 2024

  6. [6]

    S. F. Banani, H. O. Lee, A. A. Hyman, and M. K. Rosen, Nat. Rev. Mol. Cell Biol. 18, 285 (2017)

    work page 2017

  7. [7]

    Boeynaems, S

    S. Boeynaems, S. Alberti, N. L. Fawzi, T. Mit- tag, M. Polymenidou, F. Rousseau, J. Schymkowitz, J. Shorter, B. Wolozin, L. Van Den Bosch, et al., Trends Cell Biol. 28, 420 (2018)

    work page 2018

  8. [8]

    A. S. Holehouse and B. B. Kragelund, Nat. Rev. Mol. Cell Biol. 25, 187 (2024)

    work page 2024

  9. [9]

    Mohanty, U

    P. Mohanty, U. Kapoor, D. Sundaravadivelu Devarajan, T. M. Phan, A. Rizuan, and J. Mittal, Biochemistry 61, 2443 (2022)

    work page 2022

  10. [10]

    D¨ orner, M

    K. D¨ orner, M. Gut, D. Overwijn, F. Cao, M. Siketanc, S. Heinrich, N. Beuret, T. Sharpe, K. Lindorff-Larsen, and H. Maria, bioRxiv , 2024 (2024)

    work page 2024

  11. [11]

    P. Li, S. Banjade, H.-C. Cheng, S. Kim, B. Chen, L. Guo, M. Llaguno, J. V. Hollingsworth, D. S. King, S. F. Ba- nani, et al., Nature 483, 336 (2012)

    work page 2012

  12. [12]

    Zhang, S

    H. Zhang, S. Elbaum-Garfinkle, E. M. Langdon, N. Tay- lor, P. Occhipinti, A. A. Bridges, C. P. Brangwynne, and A. S. Gladfelter, Mol. Cell 60, 220 (2015)

    work page 2015

  13. [13]

    Y. Lin, D. S. Protter, M. K. Rosen, and R. Parker, Mol. Cell 60, 208 (2015)

    work page 2015

  14. [14]

    E. W. Martin, F. E. Thomasen, N. M. Milkovic, M. J. Cuneo, C. R. Grace, A. Nourse, K. Lindorff-Larsen, and T. Mittag, Nucleic Acids Res. 49, 2931 (2021)

    work page 2021

  15. [15]

    Molliex, J

    A. Molliex, J. Temirov, J. Lee, M. Coughlin, A. P. Kana- garaj, H. J. Kim, T. Mittag, and J. P. Taylor, Cell 163, 123 (2015)

    work page 2015

  16. [16]

    Maharana, J

    S. Maharana, J. Wang, D. K. Papadopoulos, D. Richter, A. Pozniakovsky, I. Poser, M. Bickle, S. Rizk, J. Guill´ en- Boixet, T. M. Franzmann,et al., Science 360, 918 (2018)

    work page 2018

  17. [17]

    P. R. Banerjee, A. N. Milin, M. M. Moosa, P. L. Onuchic, and A. A. Deniz, Angew. Chem. 129, 11512 (2017)

    work page 2017

  18. [18]

    Alshareedah, T

    I. Alshareedah, T. Kaur, J. Ngo, H. Seppala, L.-A. D. Kounatse, W. Wang, M. M. Moosa, and P. R. Banerjee, J. Am. Chem. Soc. 141, 14593 (2019)

    work page 2019

  19. [19]

    Elbaum-Garfinkle, Y

    S. Elbaum-Garfinkle, Y. Kim, K. Szczepaniak, C. C.-H. Chen, C. R. Eckmann, S. Myong, and C. P. Brangwynne, Proc. Natl. Acad. Sci. U.S.A. 112, 7189 (2015)

    work page 2015

  20. [20]

    Jawerth, E

    L. Jawerth, E. Fischer-Friedrich, S. Saha, J. Wang, T. Franzmann, X. Zhang, J. Sachweh, M. Ruer, M. Ijavi, S. Saha, et al., Science 370, 1317 (2020)

    work page 2020

  21. [21]

    Alshareedah, M

    I. Alshareedah, M. M. Moosa, M. Pham, D. A. Potoyan, and P. R. Banerjee, Nat. Commun. 12, 6620 (2021)

    work page 2021

  22. [22]

    Alshareedah, W

    I. Alshareedah, W. M. Borcherds, S. R. Cohen, A. Singh, A. E. Posey, M. Farag, A. Bremer, G. W. Strout, D. T. Tomares, R. V. Pappu, et al., Nat. Phys. , 1 (2024)

    work page 2024

  23. [23]

    A. H. Fox, S. Nakagawa, T. Hirose, and C. S. Bond, Trends Biochem.Sci. 43, 124 (2018)

    work page 2018

  24. [24]

    Marcelo, R

    A. Marcelo, R. Koppenol, L. P. de Almeida, C. A. Matos, and C. N´ obrega, Cell Death Dis.12, 592 (2021)

    work page 2021

  25. [25]

    R. Lang, R. E. Hodgson, and T. A. Shelkovnikova, Biochem. Soc. Trans. 52, 1809 (2024)

    work page 2024

  26. [26]

    Tziortzouda, L

    P. Tziortzouda, L. Van Den Bosch, and F. Hirth, Nat. Rev. Neurosci. 22, 197 (2021)

    work page 2021

  27. [27]

    Udan and R

    M. Udan and R. H. Baloh, Prion 5, 1 (2011)

    work page 2011

  28. [28]

    F. E. Loughlin and J. A. Wilce, Curr. Opin. Struct. Biol. 59, 134 (2019)

    work page 2019

  29. [29]

    Chien, C.-C

    H.-M. Chien, C.-C. Lee, and J. J.-T. Huang, Int. J. Mol. Sci. 22, 8213 (2021)

    work page 2021

  30. [30]

    A. E. Conicella, G. H. Zerze, J. Mittal, and N. L. Fawzi, Structure 24, 1537 (2016)

    work page 2016

  31. [31]

    A. E. Conicella, G. L. Dignon, G. H. Zerze, H. B. Schmidt, A. M. D’Ordine, Y. C. Kim, R. Rohatgi, Y. M. Ayala, J. Mittal, and N. L. Fawzi, Proc. Natl. Acad. Sci. 117, 5883 (2020)

    work page 2020

  32. [32]

    Li, W.-C

    H.-R. Li, W.-C. Chiang, P.-C. Chou, W.-J. Wang, and J.-r. Huang, J. Biol. Chem. 293, 6090 (2018)

    work page 2018

  33. [33]

    P. J. Lukavsky, D. Daujotyte, J. R. Tollervey, J. Ule, C. Stuani, E. Buratti, F. E. Baralle, F. F. Damberger, and F. H. Allain, Nat. Struct. Mol. Biol. 20, 1443 (2013)

    work page 2013

  34. [34]

    Afroz, E.-M

    T. Afroz, E.-M. Hock, P. Ernst, C. Foglieni, M. Jambeau, L. A. Gilhespy, F. Laferriere, Z. Maniecka, A. Pl¨ uckthun, P. Mittl, et al., Nat. Commun. 8, 45 (2017)

    work page 2017

  35. [35]

    G. C. Carter, C.-H. Hsiung, L. Simpson, H. Yang, and X. Zhang, J. Mol. Biol. 433, 166948 (2021)

    work page 2021

  36. [36]

    W. M. Babinchak, R. Haider, B. K. Dumm, P. Sarkar, K. Surewicz, J.-K. Choi, and W. K. Surewicz, J. Biol. Chem. 294, 6306 (2019)

    work page 2019

  37. [37]

    Loganathan, E

    S. Loganathan, E. M. Lehmkuhl, R. J. Eck, and D. C. Zarnescu, Front. Mol. Biosci. 6, 154 (2020)

    work page 2020

  38. [38]

    Huang, K.-F

    Y.-C. Huang, K.-F. Lin, R.-Y. He, P.-H. Tu, J. Koubek, Y.-C. Hsu, and J. J.-T. Huang, PloS one 8, e64002 (2013)

    work page 2013

  39. [39]

    J. R. Mann, A. M. Gleixner, J. C. Mauna, E. Gomes, M. R. DeChellis-Marks, P. G. Needham, K. E. Copley, B. Hurtle, B. Portz, N. J. Pyles, et al., Neuron 102, 321 (2019)

    work page 2019

  40. [40]

    Z. R. Grese, A. C. Bastos, L. D. Mamede, R. L. French, T. M. Miller, and Y. M. Ayala, EMBO Rep. 22, e53632 (2021)

    work page 2021

  41. [41]

    Ozguney, P

    B. Ozguney, P. Mohanty, and J. Mittal, Biophys. J. 123, 3844 (2024)

    work page 2024

  42. [42]

    Mohanty, J

    P. Mohanty, J. Shenoy, A. Rizuan, J. F. Mercado-Ortiz, N. L. Fawzi, and J. Mittal, Proc. Natl. Acad. Sci. U.S.A. 120, e2305625120 (2023)

    work page 2023

  43. [43]

    H. Tang, Y. Sun, L. Wang, P. C. Ke, and F. Ding, J. Chem Inf. Model. 64, 7590 (2024)

    work page 2024

  44. [44]

    G. L. Dignon, W. Zheng, Y. C. Kim, R. B. Best, and J. Mittal, PLoS Comput. Biol. 14, e1005941 (2018)

    work page 2018

  45. [45]

    R. M. Regy, G. L. Dignon, W. Zheng, Y. C. Kim, and J. Mittal, Nucleic Acids Res. 48, 12593 (2020)

    work page 2020

  46. [46]

    Tesei and K

    G. Tesei and K. Lindorff-Larsen, Open. Res. Euro. 2, 94 (2023)

    work page 2023

  47. [47]

    R. M. Regy, J. Thompson, Y. C. Kim, and J. Mittal, Protein Sci. 30, 1371 (2021)

    work page 2021

  48. [48]

    J. A. Joseph, A. Reinhardt, A. Aguirre, P. Y. Chew, K. O. Russell, J. R. Espinosa, A. Garaizar, and R. Collepardo-Guevara, Nat. Comput. Sci. 1, 732 (2021)

    work page 2021

  49. [49]

    A. R. Tejedor, A. Garaizar, J. Ram´ ırez, and J. R. Es- pinosa, Biophys. J. 120, 5169 (2021). 11

    work page 2021

  50. [50]

    H. I. Ing´ olfsson, A. Rizuan, X. Liu, P. Mohanty, P. C. Souza, S. J. Marrink, M. T. Bowers, J. Mittal, and J. Berry, Biophys. J. 122, 4370 (2023)

    work page 2023

  51. [51]

    Mohanty, A

    P. Mohanty, A. Rizuan, Y. C. Kim, N. L. Fawzi, and J. Mittal, Protein Sci. 33, e4891 (2024)

    work page 2024

  52. [52]

    Varadi, D

    M. Varadi, D. Bertoni, P. Magana, U. Paramval, I. Pidruchna, M. Radhakrishnan, M. Tsenkov, S. Nair, M. Mirdita, J. Yeo, et al., Nucleic Acids Res. 52, D368 (2024)

    work page 2024

  53. [53]

    Periole, M

    X. Periole, M. Cavalli, S.-J. Marrink, and M. A. Ceruso, J. Chem. Theory Comput. 5, 2531 (2009)

    work page 2009

  54. [54]

    Y. C. Kim and G. Hummer, J. Mol. Biol. 375, 1416 (2008)

    work page 2008

  55. [55]

    F. Cao, S. von B¨ ulow, G. Tesei, and K. Lindorff-Larsen, Protein Sci. 33, e5172 (2024)

    work page 2024

  56. [56]

    A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolin- tineanu, W. M. Brown, P. S. Crozier, P. J. in ’t Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimp- ton, Comput. Phys. Commun. 271, 108171 (2022)

    work page 2022

  57. [57]

    Ram´ ırez, S

    J. Ram´ ırez, S. K. Sukumaran, B. Vorselaars, and A. E. Likhtman, J. Chem. Phys. 133 (2010)

    work page 2010

  58. [58]

    V. A. Boudara, D. J. Read, and J. Ram´ ırez, J. Rheol. 64, 709 (2020)

    work page 2020

  59. [59]

    Rubinstein and R

    M. Rubinstein and R. H. Colby, Polymer physics (Oxford university press, 2003)

    work page 2003

  60. [60]

    Dhakal, C

    S. Dhakal, C. E. Wyant, H. E. George, S. E. Morgan, and V. Rangachari, J. Mol. Biol. 433, 166953 (2021)

    work page 2021

  61. [61]

    Watanabe, T

    F. Watanabe, T. Akimoto, R. B. Best, K. Lindorff- Larsen, R. Metzler, and E. Yamamoto, arXiv (2024)

    work page 2024

  62. [62]

    A. R. Tejedor, R. Collepardo-Guevara, J. Ram´ ırez, and J. R. Espinosa, J. Phys. Chem. B 127, 4441 (2023)

    work page 2023

  63. [63]

    Wang, P.-H

    Y.-T. Wang, P.-H. Kuo, C.-H. Chiang, J.-R. Liang, Y.-R. Chen, S. Wang, J. C. Shen, and H. S. Yuan, Journal of Biological Chemistry 288, 9049 (2013)

    work page 2013

  64. [64]

    X. Yan, D. Kuster, P. Mohanty, J. Nijssen, K. Pombo- Garc´ ıa, A. Rizuan, T. M. Franzmann, A. Sergeeva, P. M. Passos, L. George, et al., bioRxiv (2024)

    work page 2024

  65. [65]

    Sanchez-Burgos, J

    I. Sanchez-Burgos, J. R. Espinosa, J. A. Joseph, and R. Collepardo-Guevara, PLoS Comput. Biol. 18, e1009810 (2022)

    work page 2022

  66. [66]

    P. P. Gopal, J. J. Nirschl, E. Klinman, and E. L. Holzbaur, Proc. Natl. Acad. Sci. U.S.A. 114, E2466 (2017). 12 Supplementary Materials Fig. S 1. Sequence of full-length TDP-43. Positively charged, negatively charged, and aromatic amino acids are marked in blue, red, and green, respectively. Fig. S 2. Intramolecular interactions of TDP-43 (A) in the absen...

    work page 2017